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      AI adoption is accelerating expectations of what organisations should be able to do with their data. Leaders are increasingly under pressure to move quickly – to pilot, automate and experiment – while still maintaining control, trust and accountability.

      KPMG’s Alan Lavery explores how organisations can truly tap into the transformative potential of data.


      Article highlights:

      • Value constraints

        AI value is constrained by data quality, structure and governance

      • Clarity over volume

        Data clarity, not data volume, underpins effective AI adoption

      • Managing risk

        Organisations with strong data foundations move faster and manage risk more effectively


      The data and AI challenge leaders are facing

      Many leaders recognise the transformative potential of data but feel unsure about where to begin. The scale of the challenge can feel overwhelming: What systems do we have? Where is data stored now? Is our data accessible? Is the quality good enough?  

      The starting point is always clarity. Clarity on strategic intent - what competitive advantage are we looking to secure? What role data should play, and on how transformation will be sequenced.

      When you can articulate what you want to achieve - whether that’s growth, improved customer loyalty, or better utilisation of assets - it creates a foundation for every subsequent decision. Many organisations are now working with data & analytics teams to help develop data-driven strategies.

      Without strategy and alignment, data programmes can lose focus very quickly. I’ve seen initiatives get very big, very fast when goals aren’t clearly defined. The organisations that make progress most effectively are those that continually anchor their work to tangible outcomes and measurable value. 


      Why data foundations matter  

      When organisations build strong data foundations - quality, structure, accessibility, and usability - the impact can be transformative. Decision making improves and is more informed, performance becomes more transparent, personalisation becomes more meaningful, and resources are deployed more intelligently. 

      In some cases, we’ve helped organisations achieve significant improvements in productivity and efficiency by harnessing data driven insight in a disciplined, structured way. But it’s not just about efficiency; for many leaders, data is a driver of both revenue growth and resilience. 

      Much like cyber in the AI landscape, the implications of not getting it right extend far beyond technology. Getting your data into shape can make a big difference in terms of how well you understand your customers. It follows that this can lead to better selling opportunities, better products and greater levels of personalisation. What’s more, data maturity shapes confidence in decision making, the ability to innovate, and an organisation’s capacity to adapt to disruption. 


      What you need to understand 

      Building the right foundations requires sustained, intentional investment - not just a technology upgrade. You need to understand what data you have today, what’s required for tomorrow, and how your governance and access to models may need to evolve. 

      And when you get it sorted, what are you going to do with it? 

      Decisions about data storage – on premise, cloud, hybrid - directly influence your scalability, cost, security, and the speed of insight available. These choices must be aligned to the outcomes you want to achieve. 

      AI dramatically increases the value of well-structured data - but it also exposes weaknesses quicker. Data quality, lineage, accessibility, and governance have never mattered more. You’ll make the most progress when you treat data as the foundation of AI enabled improvements, not a byproduct. 


      How can leaders move from intent to action?

      You can make immediate progress by focusing on just three practical steps: 

      Be explicit about what your data goals are for the next 12–24 months. Use these to anchor every data and AI decision. 

      Map where data lives, who uses it, and how it flows. Identify the biggest gaps in quality, structure, and accessibility that hinder your AI readiness. 

      Bring technology, business, and operations together to make shared decisions on data standards, access, and use. This builds trust, accelerates adoption, and reduces risk.  


      How to realise real value from your data

      Organisations who get strong returns from data and AI tend to share three characteristics: 

      • Clear leadership framing

        Leaders articulate why data matters, how it will be used, and what good looks like. 

      • Consistent behaviours and governance

        Data is trusted, challenged, and used deliberately. Quality and usability are reinforced through everyday decisions. 

      • Integrated capability

        Technology, people, and processes work together. Platforms are modern, tools are intuitive, and AI is applied responsibly. 


      Act now to create a competitive advantage

      You don’t need perfect answers before acting, but you do need intent, direction, and clarity. 

      Data and AI are no longer future considerations - they’re reshaping decisions today. The leaders acting now are fast gaining a competitive advantage, strengthening resilience, and building organisations capable of adapting at pace. 

      Those waiting for certainty may find the gap widening faster than they expect. If you would like to find out more about how we can help you get it right on data, we’d be delighted to hear from you. 

      Alan Lavery

      Managing Director, Applied Intelligence, GenAI Lead

      KPMG in Ireland


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